TADCompare: Differential TAD boundary detection

Description Usage Arguments Details Value Examples

View source: R/TADCompare.R

Description

Differential TAD boundary detection

Usage

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TADCompare(
  cont_mat1,
  cont_mat2,
  resolution = "auto",
  z_thresh = 2,
  window_size = 15,
  gap_thresh = 0.2,
  pre_tads = NULL
)

Arguments

cont_mat1

Contact matrix in either sparse 3 column, n x n or n x (n+3) form where the first three columns are coordinates in BED format. See "Input_Data" vignette for more information. If an n x n matrix is used, the column names must correspond to the start point of the corresponding bin. Required.

cont_mat2

Second contact matrix, used for differential comparison, must be in same format as cont_mat1. Required.

resolution

Resolution of the data. Used to assign TAD boundaries to genomic regions. If not provided, resolution will be estimated from column names of matrix. If matrices are sparse, resolution will be estimated from the column names of the transformed full matrix. Default is "auto"

z_thresh

Threshold for differential boundary score. Higher values result in a higher threshold for differential TAD boundaries. Default is 2.

window_size

Size of sliding window for TAD detection, measured in bins. Results should be consistent regardless of window size. Default is 15.

gap_thresh

Required % of non-zero interaction frequencies for a given bin to be included in the analysis. Default is .2

pre_tads

A list of pre-defined TADs for testing. Must contain two entries with the first corresponding to TADs detected in matrix 1 and the second to those detected in matrix 2. Each entry must contain a BED-like data frame or GenomicRanges object with columns "chr", "start", and "end", corresponding to coordinates of TADs. If provided, differential TAD boundaries are defined only at these coordinates. Optional.

Details

Given two sparse 3 column, n x n , or n x (n+3) contact matrices, TADCompare identifies differential TAD boundaries. Using a novel boundary score metric, TADCompare simultaneously identifies TAD boundaries (unless provided with the pre-defined TAD boundaries), and tests for the presence of differential boundaries. The magnitude of differences is provided using raw boundary scores and p-values.

Value

A list containing differential TAD characteristics

Examples

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# Read in data
data("rao_chr22_prim")
data("rao_chr22_rep")
# Find differential TADs
diff_frame <- TADCompare(rao_chr22_prim, rao_chr22_rep, resolution = 50000)

cresswellkg/TADCompare documentation built on Dec. 1, 2020, 10:35 p.m.